Reprint
Corporate Bankruptcy Prediction
International Trends and Local Experience
Edited by
June 2020
202 pages
- ISBN978-3-03928-911-0 (Paperback)
- ISBN978-3-03928-912-7 (PDF)
This book is a reprint of the Special Issue Modern Methods of Bankruptcy Prediction that was published in
Business & Economics
Computer Science & Mathematics
Summary
Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy.
Format
- Paperback
License
© 2020 by the authors; CC BY-NC-ND license
Keywords
ISA 701; audit expectation gap; key audit matters; materiality; Poland; corporate bankruptcy; forecasting; fuzzy sets; artificial neural networks; decision trees; bankruptcy prediction; tax arrears; payment defaults; financial ratios; failure; bankruptcy; chapter 11; regression count; meta-analysis; literature review; manufacturing insolvency; prediction; citation mining; bankruptcy prediction; classification; credit risk modelling; corporate failure; rating systems; bankruptcy prediction; ensemble classifiers; boosting; bagging; stacking; scoring models; bankruptcy; insolvency; financial distress; default; failure; forecasting methods; models predicting financial distress; phases of economic cycle; Czech Republic; European large companies; bankruptcy risk; company performance; bankruptcy prediction; Principal Component Analysis; neural networks; support vector machine; bankruptcy model; prediction; bankruptcy